基于节点特征和相邻节点推荐的WSN信任评估

Shaik Sahil Babu, Arnab Raha, M. K. Naskar
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引用次数: 27

摘要

在无线传感器网络(WSNs)中,传统的安全加密机制对大内存、高处理速度和通信带宽等资源的消耗较高。此外,它们无法检测到在数据包路由过程中导致网络崩溃的错误、恶意和自私节点。因此,加密安全机制不足以在众多相邻节点中选择合适的节点,以实现数据包从源到接收的安全路由。另外,信任管理方案是评估节点信任的工具,从而选择一个节点进行路由,并检测它们的意外节点行为(错误或恶意)。在本文中,我们提出了一种基于节点的QoS特征(信任度量)和相邻节点推荐的新的信任评估方法TENCR。该方法比基于算术平均的方法更有效地检测恶意和自私节点,并允许可信节点进行路由,从而消除恶意/自私节点。我们提出的信任评估方法具有自适应和节能的特点,该方法将可信任节点分离出来,使其有资格参与路由,而将其他节点排除为恶意/自私节点。因此,在路由中只允许可信节点,而恶意/自私节点将被自动淘汰。
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Trust Evaluation Based on Node’s Characteristics and Neighbouring Nodes’ Recommendations for WSN
In Wireless Sensor Networks (WSNs), the traditional cryptographic mechanisms for security require higher consumption of resources such as large memory, high processing speed and communication bandwidth. Also, they cannot detect faulty, malicious and selfish nodes which lead to the breakdown of network during packet routing. Hence, cryptographic security mechanisms are not sufficient to select appropriate nodes among many neighbouring nodes for secure packet routing from source to sink. Alternatively, trust management schemes are tools to evaluate the trust of a node and thereby choosing a node for routing, and also detecting their unexpected node behaviour (either faulty or malicious). In this paper, we propose TENCR: a new Trust Evaluation method based on the Node’s QoS Characteristics (trust metrics) and neighbouring nodes' Recommendations. The proposed new technique detects the malicious and selfish nodes very efficiently than the arithmetic mean based methods, and allows trustworthy nodes in routing, thereby eliminating malicious/selfish nodes. Our proposed trust evaluation method is adaptive and energy efficient that separates the trustworthy nodes and qualify them to take the participation in routing, and disqualify the other nodes as malicious/selfish. Hence, trustworthy nodes only be allowed in routing, and malicious/selfish nodes will be eliminated automatically.
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